基于纹理度划分的医学图像可逆信息隐藏方法

针对目前具有对比度增强效果的可逆信息隐藏（RDH）算法大多受到嵌入率的影响，未能实现较好的对比度增强效果的问题，提出一种基于纹理度划分的医学图像可逆信息隐藏方法。首先，通过对比度拉伸的方法实现医学图像对比度增强；然后，再利用医学图像纹理度的自身特点，将医学图像划分为高、低两类纹理度等级，其中高纹理度等级构成医学图像的关键部分；最后，为了进一步增强高纹理度等级的对比度并保证信息嵌入率，对不同的纹理度等级像素采用不同的嵌入方法。为了与其他具有对比度增强效果的医学图像可逆信息隐藏算法比较载密图像的对比度增强效果，采用了针对对比度失真的无参考图像质量评价标准（NR-CDIQA）作为实验客观依据。实验结果表明，在不同嵌入率下，使用所提方法的载密图像的NR-CDIQA值更高，对比度增强效果更好。

Reversible data hiding method based on texture partition for medical images

To solve the problem that contrast enhancement effect is affected by the embedding rate in most existing Reversible Data Hiding (RDH) algorithms, a new RDH method based on texture partition for medical images was proposed. Firstly, the contrast of an image was stretched to enhance image contrast, and then according to the characteristics of medical image texture, the medical image was divided into high and low texture levels. The key partion of the medical image mainly had high texture level. To enhance the contrast of high texture level further and guarantee the infomation embedding capacity, different embedding processes were adopted for high and low texture levels. In order to compare the effect of contrast enhancement between the proposed method and other RDH algorithms for medical images, No-Reference Contrast-Distorted Images Quality Assessment (NR-CDIQA) was adopted as the evaluation standards. The experimental results show that the marked images processed by the proposed method can get better NR-CDIQA and contrst enhancement in different embedding rate.